Impact of physician and center case volume on the adequacy of cardiac monitoring during adjuvant trastuzumab in breast cancer.
Bibliographic record
Abstract
128 Background: A recent study suggests that cardiotoxicity from adjuvant trastuzumab (T-mab) is associated with inadequate cardiac monitoring (Ng et al. SABCS 2012). Few studies have examined the impact of centre or physician (MD) case volume (vol) on the quality of care in systemic therapy, including the adequacy of cardiac monitoring during T-mab treatment. Methods: All breast cancer patients treated with adjuvant T-mab in Ontario between 2003-2009 were identified through a provincial drug funding program. Patient demographics, hospitalizations, cardiac risk factors, cardiac imaging, comorbidities, treatment centres and MDs were ascertained. Annual case vol was calculated as the number of patients treated per year with adjuvant T-mab by each MD and centre. Cumulative case vol was calculated as the total number of patients treated with adjuvant T-mab. Centre and MD vol were divided into terciles (T1, T2 and T3) by the year of diagnosis. Inadequate cardiac monitoring was defined as per recent guidelines and per Ng et al. Hierarchical multivariable logistic regression models were constructed to examine factors associated with inadequate cardiac monitoring. Results: Our cohort consisted of 3,777 patients, 214 MDs and 68 centres. Of the total patients, 16.5% were over age 65; 30.3%, 9.4%, and 1.2% had previous diagnoses of hypertension, diabetes, and heart failure (HF), respectively; 24.3% did not receive adequate cardiac monitoring. Inadequate cardiac monitoring was associated with lower cumulative MD vol (T1: 27.9%, T2: 23.3%, T3: 20.8%, p < 0.0001) and lower annual centre vol (T1: 32.5%, T2: 19.7%, T3: 20.7%, p < 0.0001) in univariate analyses, and remained significant after adjusting for age, comorbidities, previous HF, socioeconomic status based on income, rural residence and calendar period. After adjusting for patient clustering at the MD, centre, and regional levels, lower cumulative MD vol (p=0.012), but not annual centre vol, remained a significant predictor for inadequate cardiac monitoring. Conclusions: Our findings suggest improved cardiac monitoring with greater MD experience, supporting the notion of centralization of systemic therapy to high vol MDs to optimize outcomes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".